David Tellez
David Tellez
PhD student, Department of Pathology, Radboudumc
Verified email at radboudumc.nl - Homepage
Cited by
Cited by
Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer
BE Bejnordi, M Veta, PJ Van Diest, B Van Ginneken, N Karssemeijer, ...
Jama 318 (22), 2199-2210, 2017
Predicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge
M Veta, YJ Heng, N Stathonikos, BE Bejnordi, F Beca, T Wollmann, ...
Medical image analysis 54, 111-121, 2019
Whole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional Networks
D Tellez, M Balkenhol, I Otte-Höller, R van de Loo, R Vogels, P Bult, ...
IEEE Transactions on Medical Imaging, 12, 2018
Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology
D Tellez, G Litjens, P Bandi, W Bulten, JM Bokhorst, F Ciompi, ...
Medical Image Analysis 58, 101544, 2019
Neural image compression for gigapixel histopathology image analysis
D Tellez, G Litjens, J van der Laak, F Ciompi
IEEE transactions on pattern analysis and machine intelligence, 2019
Deep learning assisted mitotic counting for breast cancer
MCA Balkenhol, D Tellez, W Vreuls, PC Clahsen, H Pinckaers, F Ciompi, ...
Laboratory Investigation 99 (11), 1596-1606, 2019
H and E stain augmentation improves generalization of convolutional networks for histopathological mitosis detection
D Tellez, M Balkenhol, N Karssemeijer, G Litjens, J van der Laak, ...
Medical Imaging 2018: Digital Pathology 10581, 105810Z, 2018
Deep learning and manual assessment show that the absolute mitotic count does not contain prognostic information in triple negative breast cancer
MCA Balkenhol, P Bult, D Tellez, W Vreuls, PC Clahsen, F Ciompi, ...
Cellular Oncology 42 (4), 555-569, 2019
Predicting arousal with machine learning of EEG signals
T Nagy, D Tellez, Á Divák, E Lógó, M Köles, B Hámornik
2014 5th IEEE Conference on Cognitive Infocommunications (CogInfoCom), 137-140, 2014
Virtual staining for mitosis detection in Breast Histopathology
C Mercan, G Mooij, D Tellez, J Lotz, N Weiss, M van Gerven, F Ciompi
2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 1770-1774, 2020
Extending Unsupervised Neural Image Compression With Supervised Multitask Learning
D Tellez, D Höppener, C Verhoef, D Grünhagen, P Nierop, M Drozdzal, ...
Medical Imaging with Deep Learning, 770-783, 2020
Gigapixel whole-slide image classification using unsupervised image compression and contrastive training
D Tellez, J van der Laak, F Ciompi
Neural image compression for non-small cell lung cancer subtype classification in H&E stained whole-slide images
W Aswolinskiy, D Tellez, G Raya, L van der Woude, M Looijen-Salamon, ...
Medical Imaging 2021: Digital Pathology 11603, 1160304, 2021
Deep learning enables fully automated mitotic density assessment in breast cancer histopathology
M Balkenhol, P Bult, D Tellez, W Vreuls, P Clahsen, F Ciompi, ...
European Journal of Cancer 138, S86, 2020
Learning Unsupervised Knowledge-Enhanced Representations to Reduce the Semantic Gap in Information Retrieval
M Agosti, S Marchesin, G Silvello
ACM Transactions on Information Systems (TOIS) 38 (4), 1-48, 2020
Deep learning enables fully automated mitotic density assessment in breast cancer histopathology
M Balkenhol, P Bult, D Tellez, W Vreuls, P Clahsen, F Ciompi, ...
VIRCHOWS ARCHIV 475, S58-S59, 2019
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